Presented By:
Ed teNyenhuis
Hitachi ABB Power Grids Canada
TechCon 2021
Abstract
Power transformers are a very critical component of the power grid. Most were installed in the 1960’s and 1970’s and thus have an average age of 40+ years for most utilities. It will not be possible to replace all these transformers in the near term so life extension through targeted maintenance will be vital to maintain high reliability. Transformer Asset Management is a detailed technical evaluation that includes models for all failure mechanisms and determines a single risk of failure per transformer utilizing test results and online transformer monitoring. Individual transformers can be compared within an entire fleet or group. The impact of transformer condition changes can then be simulated with maintenance actions to achieve the largest overall fleet improvement for the limited maintenance resources. The background of Transformer Asset Management will be presented along with various maintenance actions and case studies. It will be shown in the paper that a well-designed asset management program will quantify transformer risk of failure so that economic planning for overall maximum benefit to the assets can be done.
Introduction
Power transformers are the backbone of the North American power grid and there is an ever-increasing need for progressive management of these important assets. Most transformers operate for decades with minimal attention however the age distribution is such that the majority were installed in the 1960’s and 1970’s. For most utilities, the average age of transformers is 40+ years and with many transformers that are 60+ years of age. A replacement rate of 2 – 3% per year is the range of what is practically possible due to financial, personnel and outage limitations. Most of these aged assets will have to remain in service for more years to come, increasing the vital importance of transformer asset management.
Some transformers are also being utilized in a manner different than originally planned due to increased distributed loads and impact of renewables (power flows in different directions and more varying load).
The knowledge about these aging transformer assets may also have been reduced due to retirement of experienced staff or personnel turnover. The viability of spare transformers is sometimes not known due to poor maintenance or unknown condition.
Transformer asset management involves performing a technical evaluation of the transformer fleet to highlight the transformers requiring higher levels of attention. Based on this, limited maintenance budgets and limited replacements can be planned to best achieve overall fleet improvement. Transformers do not all need the same amount of maintenance and some utilities will learn to redistribute maintenance spending among transformers without reducing the reliability of their fleet.
It will be shown that a well-designed asset management program will quantify transformer risk of failure so that economic planning for overall maximum benefit to the assets can be done.
Technical Background – Transformer Failure Modes
Comparison of transformers is done by the calculation of individual risk of failure per year for each transformer. This should be a consistent methodology that considers all factors including transformer condition, design, failure history, loading, maintenance, its operating environment, reclosing practices and so on. The results are calibrated to actual failure statistics. There is also an importance factor determined for each transformer which essentially compares the impact of failure of transformers (a higher number is a bigger impact).
The risk of failure is based on what causes transformers to fail: winding thermal failure, winding dielectric failure, winding short circuit failure, failure of accessories (such as tap-changer, bushing, cooling) and random / localized risks (such as seismic, high occurrence of lightning, geometric induced current etc.). These are described in more detail below.
Winding Short Circuit Failure – This is caused by an external fault that in turn causes very high short circuit currents in the windings – this gives rise to mechanical forces and temperature rise. The mechanical forces are electromagnetic and have a radial and axial component – see Figure 1 below. Examples of radial and axial force failures are shown respectively in Figure 2. Transformers are designed to withstand short circuit current, but older transformers may not have had as high a level of accuracy in its design calculations or benefited from modern materials (i.e., harder copper or high density pressboard). The short circuit strength can be diminished over time by recurring through faults (and inrush currents).
Winding Dielectric Failure – Overvoltage or a transient voltage can cause dielectric failure in transformer windings – an example is shown in Figure 3 below. The risk of dielectric failure is affected by the design dielectric strength, the factory high voltage testing that was originally done, location (near lightning prone areas), arrestor type, dissipation factor of the insulation, oil quality results and dissolved gases in the oil.
Winding Thermal Failure – Thermal degradation of the transformer insulation due to overloading or deterioration of cooling can eventually lead to transformer failure – see Figure 4. Cellulose aging occurs due to normal loading but is accelerated by high insulation temperature, humidity and oxygen. This is quantified by Degree of Polymerization (DP) which is a measure of the number of intact molecular furan chains in a cellulose fiber. The DP value can be determined by a direct paper sample however this is normally not done due to the destructive nature of taking the sample from the exact highest temperature location. The DP value can be estimated from cellulose aging byproducts such as carbon oxides or furans from the oil. Aged cellulose can lead more easily to dielectric or mechanical failure.
Accessory Failure – Failures or malfunction of bushings, tap changers, auxiliary equipment or cooling can lead to overall transformer failure or damage. Accessories account for a large percentage of transformer failures.
Random failure – This includes the other factors not included above such as seismic risk, static electrification risk, excessive pollution environment, etc.
Technical models have been created for each of the above risk categories and they are combined using probabilistic methods to determine a single risk of failure number for each transformer. In this manner, a fleet of transformers can be compared and evaluated. Figure 5 shows the accumulation of the individual risk categories and see Figure 6 for an example of total risk of failure on the X axis versus importance factor on the Y axis for a fleet of transformers.
While much of the data for the risk of failure calculation is from sampling or off-line testing, the recent emergence of on-line monitoring for gas in oil, bushing power factor, temperature, partial discharge, etc. enhances the depth of the calculation. It is also now possible to build in the risk of failure models into the on-line monitoring so that the risk of failure is calculated in real time – an example of a fleet assessment dashboard is shown below in Figure 7. The impact of transformer condition changes can then be seen immediately in the risk of failure of the transformer and its ranking compared to the rest of the fleet.
Transformer Asset Management Methodology
The recommended steps for performing transformer asset management are as follows:
- Gather historical information on the transformer assets including past maintenance done, electrical tests, dissolved gas in oil tests, oil physical tests, factory test reports and thermal scans.
- Perform a visual inspection of each transformer and note items such as leaks, temperature gauge readings, liquid level gauge readings, tank pressure (if sealed unit), silica gel condition, bushing condition, surge arrester count, control cabinet condition, fan operation, tapchanger count etc.
- Gather online monitor data if available (gas, bushing, partial discharge)
- Determine an importance value for each transformer based on the impact of a failure (1 to 100 where 100 is the highest importance).
- Enter the data into a fleet assessment tool.
- Calculate the risk of failure for each transformer.
- Assemble the fleet distribution risk of failure.
- Determine maintenance actions to reduce the highest risk of failure units
- Update the risk of failure as large corrective actions are done (i.e, every 1 – 2 years)
There are a wide range of maintenance actions that will reduce the risk of failure of a transformer. To diagnose a transformer problem, this could include internal inspections, advanced electrical testing, high voltage testing or OEM design study. For understood problems, this could include oil reclaiming, transformer dryout, bushing replacement, operating temperature reduction, leak reduction, tap-changer replacement, off circuit tap-changer hard wiring, cooling repairs and so on. Properly targeted maintenance actions extend the life of transformer assets and increase the reliability of an overall transformer fleet.
Several recent fleet case studies will be presented in the next sections to demonstrate best practice methods for asset management.
Case Study # 1
A very large 40-year-old, hydroelectric station with approximately 40 transformers was experiencing an increasing number of costly transformer failures. A detailed technical fleet assessment determined the individual risk of failure and a 10-year investment plan was prepared for replacement of about 1/3 of the assets and targeted maintenance to extend the life of the other assets to postpone the very large investment of total transformer replacement. The overall site reliability improved significantly throughout the program implementation.
The fleet assessment was updated annually so that the improved overall risk of failure was seen, and the impact of spending was confirmed. The targeted maintenance for the following year could also be planned. This is shown in Figure 8.
Case Study # 2
Another case is a fleet of smaller transformers (less than 50 MVA) where the fleet assessment showed that only a small number of the transformers needed replacement and that specific & planned maintenance actions over the next 5 years could accomplish the desired fleet improvement for a lower cost. This was different than the original expectation where it was assumed most of the transformers required replacement due to their age. The chart is shown below in Figure 9.
This demonstrates that transformer asset management can optimize maintenance spending and extend the life of assets in order to postpone or long-term plan replacement spending.
Conclusions
Transformer Asset Management is a detailed technical evaluation that includes models for all failure mechanisms and determines a single risk of failure per transformer utilizing test results and online transformer monitoring. Individual transformers can be compared within an entire fleet or group.
The impact of transformer condition changes can then be simulated with maintenance actions to achieve the largest overall fleet improvement for the limited maintenance resources.
Two case studies were shown to demonstrate that Transformer Asset Management can reduce the fleet failure rate and better manage maintenance and replacement cost spending.
It was shown that a well-designed asset management program will quantify transformer risk of failure so that economic planning for overall maximum benefit to the assets can be done.
References
